Prostate cancer is the second most commonly diagnosed cancer worldwide. Although androgen deprivation therapy initially demonstrates clinical benefit, disease relapse with more aggressive phenotypes f Show more
Prostate cancer is the second most commonly diagnosed cancer worldwide. Although androgen deprivation therapy initially demonstrates clinical benefit, disease relapse with more aggressive phenotypes frequently occurs. The acidic tumor microenvironment in solid tumors may alter drug responsiveness. This study investigates how extracellular pH influences the cytotoxic effects of bicalutamide in human prostate cancer cell lines. PC3 and LNCaP cells were exposed to bicalutamide at varying concentrations at pH 7.4 and pH 6.8. IC50 values were determined using the MTT assay. Cell migration, apoptosis, and cell cycle distribution were evaluated by wound-healing assay, annexin V/PI staining, and DNA content analysis, respectively. The expression of Bicalutamide (140 μg/mL) reduced PC3 cell viability to 39.62% at pH 7.4 compared with 51.36% at pH 6.8. In LNCaP cells, viability declined to 33.64% at pH 7.4% and 56.09% at pH 6.8. Treated PC3 cells exhibited significantly greater migration at pH 6.8 ( The efficacy of bicalutamide in prostate cancer cells is significantly influenced by extracellular pH. The drug exerts stronger cytotoxic, antimigratory, and proapoptotic effects at physiological pH (7.4) compared with acidic conditions (6.8). Show less
Single-cell omics technology is a powerful tool in biomedical research. However, single cell proteomics has lagged due to an inability to amplify peptides in a similar fashion to nucleotide strings. S Show more
Single-cell omics technology is a powerful tool in biomedical research. However, single cell proteomics has lagged due to an inability to amplify peptides in a similar fashion to nucleotide strings. Single cell proteomics is important because proteins are the main functional unit in cells, and they often poorly correlate with mRNA quantities. In this paper we describe the first single cell proteomic analysis of complex tissue, comparing aneurysmal and normal mouse aorta from males and females. We also compare and integrate our single cell proteomic profiles with a matching single cell transcriptomics dataset. We compared single cell proteomes between male and female, wild-type and We identified all major aortic cell types including 7 distinct smooth muscle cell subtypes. The proportion of these cells varied based on sex and the Single cell proteomics identified new subpopulations of vascular smooth muscles cells and novel cell type specific protein signatures related to sex differences and aneurysm formation. Next generation sequencing (NGS), Mass spectrometer (MS), Single cell proteomics by Mass Spectrometry (ScOPE-MS), Marfan's syndrome (MFS), Fibrillin 1 (FBN1), Transforming growth factor β (TGFβ), Smooth muscle cell (SMC), Single cell proteomic (scProteomic), Differentially expressed proteins (DEPs), Wild-type (WT), Hanks' balanced salt solution (HBSS), Fetal bovine serum (FBS), Dulbecco's Modified Eagle Medium (DMEM), Data-independent acquisition parallel accumulation-serial fragmentation (DIA-PASEF), Magnetic assisted cell sorted (MACS), Single Cell Analysis in Python (Scanpy), Kyoto Encyclopedia of Genes and Genomes (KEGG), Principal component analysis (PCA), Uniform manifold projection (UMAP), Single cell transcriptomic (scTranscriptomic), Smoothelin (Smtn), Transgelin (Tagln), Myosin heavy chain 11 (Myh11), Platelet endothelial cell adhesion molecule 1 (Pecam1), Dipeptidase 1 (Dpep1), Uncoupling protein 1 (Ucp1), Low-density lipoprotein receptor-related protein (Lrp1), DNA ligase 3 (Lig3), Capsaicin channel transient receptor potential vanilloid 1 (Trpv1), Endothelial to mesenchymal transition (endMT), Intercellular adhesion molecule 1 (Icam1), Intercellular adhesion molecule 2 (Icam2), Endothelial cell-selective adhesion molecule (Esam), Calponin 1 (Cnn1), Vimentin (Vim), Zinc finger E-box-binding homeobox 1 (Zeb1), Snail family transcriptional repressor 1 (Snai1), Tropomyosin alpha-4 chain (Tpm4), Angiotensin converting enzyme (Ace). Show less
DNA-methylation profiles have been used successfully to develop highly accurate biomarkers of age, epigenetic clocks, for many species. Using a custom methylation array, we generated DNA methylation d Show more
DNA-methylation profiles have been used successfully to develop highly accurate biomarkers of age, epigenetic clocks, for many species. Using a custom methylation array, we generated DNA methylation data from n = 238 porcine tissues including blood, bladder, frontal cortex, kidney, liver, and lung, from domestic pigs (Sus scrofa domesticus) and minipigs (Wisconsin Miniature Swine™). Samples used in this study originated from Large White X Landrace crossbred pigs, Large White X Minnesota minipig crossbred pigs, and Wisconsin Miniature Swine™. We present 4 epigenetic clocks for pigs that are distinguished by their compatibility with tissue type (pan-tissue and blood clock) and species (pig and human). Two dual-species human-pig pan-tissue clocks accurately measure chronological age and relative age, respectively. We also characterized CpGs that differ between minipigs and domestic pigs. Strikingly, several genes implicated by our epigenetic studies of minipig status overlap with genes (ADCY3, TFAP2B, SKOR1, and GPR61) implicated by genetic studies of body mass index in humans. In addition, CpGs with different levels of methylation between the two pig breeds were identified proximal to genes involved in blood LDL levels and cholesterol synthesis, of particular interest given the minipig's increased susceptibility to cardiovascular disease compared to domestic pigs. Thus, breed-specific differences of domestic and minipigs may potentially help to identify biological mechanisms underlying weight gain and aging-associated diseases. Our porcine clocks are expected to be useful for elucidating the role of epigenetics in aging and obesity, and the testing of anti-aging interventions. Show less